Fixes for DisTorch V2 LoRA loading as well as sticky allocations when using standard loader

README.md

@@ -1,11 +1,11 @@
-# ComfyUI-MultiGPU v2.0.0: Universal .safetensors and GGUF Multi-GPU Distribution with DisTorch
+# ComfyUI-MultiGPU v2: Universal .safetensors and GGUF Multi-GPU Distribution with DisTorch
 <p align="center">
   <img src="https://raw.githubusercontent.com/pollockjj/ComfyUI-MultiGPU/main/assets/distorch_average.png" width="600">
   <br>
   <em>Free almost all of your GPU for what matters: Maximum latent space processing</em>
 </p>
 
-## The Core of ComfyUI-MultiGPU v2.0.0:
+## The Core of ComfyUI-MultiGPU v2:
 [^1]: This **enhances memory management,** not parallel processing. Workflow steps still execute sequentially, but with components (in full or in part) loaded across your specified devices. *Performance gains* come from avoiding repeated model loading/unloading when VRAM is constrained. *Capability gains* come from offloading as much of the model (VAE/CLIP/UNet) off of your main **compute** device as possible—allowing you to maximize latent space for actual computation.
 
 1.  **Universal .safetensors Support**: Native DisTorch2 distribution for all `.safetensors` models.

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-multigpu"
 description = "Provides a suite of custom nodes to manage multiple GPUs for ComfyUI, including advanced model offloading for both GGUF and Safetensor formats with DisTorch, and bespoke MultiGPU support for WanVideoWrapper and other custom nodes."
-version = "2.0.1"
+version = "2.1.0"
 license = {file = "LICENSE"}
 
 [project.urls]